Layer thickness is a critical part of the flexible pavement system. It can affect the structural capacity of existing flexible pavement, and can be used to predict its remaining service life. For newly constructed flexible pavement, obtaining its layer thickness is essential for the purposes of quality control and quality assurance (QC/QA).
Currently, most departments of transportation, highway agencies, and consultants in the United States use destructive methods, e.g. coring, to obtain asphalt pavement layer thicknesses. As a non-destructive technique, ground penetration radar (GPR) has also been applied to estimate asphalt pavement thickness. However, the use of GPR is limited due to the difficulty involved in determining the dielectric constant of asphalt pavement in the traditional two-way travel time and surface reflection method. Asphalt mixture is a composite material and, as such, the reflection amplitude of electromagnetic waves could be affected by many factors, such as the presence of moisture. The extended common mid-point (XCMP) method is an alternative method that can be used on the traditional air-coupled pulsed horn antenna to increase the accuracy of asphalt pavement thickness estimation without calibrating the dielectric constant by taking cores. By developing signal processing and numerical analysis techniques, this research attempts to integrate 3-D GPR with the XCMP method, which holds certain advantages over the traditional air-coupled pulsed horn antenna.
3-D GPR is a multi-array stepped-frequency radar that can measure both in-line and cross-line directions at a very close sampling interval. Therefore, 3-D radar provides faster data collection speeds than the pulsed horn antenna and is preferred in large survey areas such as an airport runway/taxiway. To solve the XCMP equations, the time domain sampling rate of the 3-D radar is increased by applying a Whittaker-Shannon interpolation. The XCMP equations are then solved numerically in the least-square sense.
By validating the developed algorithm in a full scale test site, the study concludes that by using signal processing techniques and numerical analysis approaches, 3-D radar can be used to accurately predict asphalt layer thickness using the XCMP method when the layer thickness is greater than 50mm.